2015-03-25T04:21:57ZAssesment Of Air Quality And Anthropogenic Aerosol Fraction Over India Using Observations And Modelhttp://hdl.handle.net/2005/2418
Title: Assesment Of Air Quality And Anthropogenic Aerosol Fraction Over India Using Observations And Model
Authors: Srivastava, Nishi
Abstract: Air quality degradation is emerging to be an issue of major concern in India. Recent investigations have shown that anthropogenic aerosols have significant impact on climate as well as on health. In fourth assessment report of IPCC, it has been mentioned that radiative effects of anthropogenic aerosols constitute one of the major uncertainties in assessing aerosol-induced climate impact. In addition to climate impacts, aerosol causes respiratory and cardiovascular diseases, air quality degradation, acidification of aquatic and terrestrial ecosystems. Characterization of anthropogenic aerosol fraction (defined as the fraction of anthropogenic aerosols to composite aerosols) is an appealing topic of research in current scenario. The first step towards achieving this goal is to separate natural aerosol from composite aerosols, which is a complex task. The main objective of this thesis work is the assessment of air quality and anthropogenic aerosol fraction over India using observations (ground-based as well as satellite-based) and chemistry-transport model. Specifically objectives are (a) assessment of air quality and anthropogenic aerosol fraction over Indian region (b) develop a method to derive natural aerosol properties over land and oceans using multi-satellite data analysis, which is first step towards separating natural aerosol effects from its anthropogenic counter parts and (c) evaluate performance of CHIMERE chemistry-transport model for Indian region and validate its suitability to air quality studies over India. In this thesis, different approaches have been followed such as ground-based observations, multi-satellite data analysis and CHIMERE transport model. We have used multi-year observations of particulate mass (PM) concentration, aerosol black carbon (BC) mass concentration and aerosol optical depth (AOD) from a network of observatories to make an assessment of ambient air quality over India. First, we have developed a method to estimate dust and sea-salt optical depth using multi-satellite data analysis. This enabled the determination of anthropogenic aerosol fraction over land and ocean and we have validated this method by comparing against observations. Surprisingly, even over desert locations in India and Saudi Arabia, the anthropogenic fraction were unexpectedly high (~0.3 to 0.4) and the regionally averaged anthropogenic fraction over India was 0.620.06 (for the year 2004). The CHIMERE chemistry-transport model was used to simulate PM, BC and AOD over India and are compared with measurements. Evaluation of CHIMERE output shows that diurnal and seasonal trends are captured reasonably well by the model. It was found that absolute magnitudes differ substantially during monsoon months. Model simulations are also used to estimate anthropogenic fraction over Indian region and are compared with observations. Implications of the results are discussed.
Mineral dust constitutes the single largest contributor of natural aerosols over continents. The first step towards separating natural aerosol radiative impact from its anthropogenic counterparts over continents is to gather information on dust aerosols. The infrared (IR) radiance (10.5–12.5 mm) acquired from the Kalpana satellite (8-km resolution) was used to retrieve regional characteristics of dust aerosols over the Afro-Asian region during the winter of 2004, coinciding with a national aerosol campaign. Here, we used aerosol-induced IR radiance depression as an index of dust load. The regional distribution of dust over various arid and semi-arid regions of India and adjacent continents has been estimated, and these data in conjunction with regional maps of column aerosol optical depth (AOD) are used to infer anthropogenic aerosol fraction. Surprisingly, even over desert locations in India and Saudi Arabia, the anthropogenic fraction were relatively high (0.3 to 0.4) and the regionally averaged anthropogenic fraction over India was 0.62 ±0.06.
Sea-salt constitutes the single largest contributor of natural aerosols over oceans. We derive sea-salt aerosol distribution using a method utilizing multi-satellite data analysis. This information was used in conjunction with dust aerosols retrieval to calculate anthropogenic fraction over land and ocean. First, we derived a relation between MODIS AOD and NCEP wind speed at the sea-surface. An exponential increase in AOD as a function of wind speed was observed from mid of southern ocean to northern Arabian Sea. Latitudinal variation of wind independent component of optical depth (τ0) and wind index (b) was used to estimate the sea-salt optical depth over Arabian Sea. The value of τ0 showed an exponential increase as we move towards north from 35°S while b showed linear increase. The derived relations for the τ0 and b have been used to derive the sea-salt AOD distribution over oceanic regions in the domain (Eq-30°N; 30°E-110°E). Then we subtract the natural aerosol contribution from composite AOD data from MISR to obtain anthropogenic aerosol fraction. Over Indian region, high anthropogenic fraction was observed over northern belt specifically Indo-Gangetic Plains (IGP). Annually averaged anthropogenic fraction over Indian domain (4N-29.5N; 67E-88.5E) is ~0.43. Further, we have investigated the impact of sea-surface winds on sea-salt radiative effect in visible and infrared region with the help of SBDART radiative transfer model. The SBDART simulations have shown that at 15 m s-1, sea-salt induced shortwave cooling at the sea-surface was -86 W m-2.
Derivation of anthropogenic aerosol fraction over whole Indian domain has demonstrated the importance of anthropogenic aerosols. This observation motivated us to examine the air quality over Bangalore, a fast growing city in India. We have analyzed data from ground based measurements of particulate matter, observations from satellites and also model simulations. Comparison with national threshold indicates that more than 50% of observations were above the residential threshold. To represent the air quality of Bangalore we have calculated the air quality index (AQI) for air pollutants. Coarse spatial and temporal resolution of observational data is one major shortcoming in such analysis. Therefore, satellite observations are alternative to quantify the air quality over large area. We have used MODIS AOD and RSPM to develop an empirical relation between these two parameters. A reasonably good agreement was observed between measured RSPM and RSPM derived using satellite data (by applying empirical relation).
The CHIMERE chemistry-transport model was used to simulate PM, BC and AOD over India and are compared with measurements. Evaluation of CHIMERE output shows that diurnal and seasonal trends are captured reasonably well by the model. It was found that absolute magnitudes differ substantially during pre-monsoon and monsoon months. Model simulations are also used to estimate anthropogenic fraction over Indian region and are compared with observations. Implications of the results and future scope are discussed. The validation of model results suggests that CHIMERE model is suitable for simulating air quality over India with reasonable accuracy. This would in turn help us to address the impacts of air pollution on regional climate and help policy makers in order to reduce the air pollution.
In summary, we have developed a new method to infer natural aerosol (sea-salt and dust) properties using multi-satellite data analysis. This technique has been applied to derive anthropogenic aerosol fraction over Indian region. Surprisingly, even over desert locations in India and Saudi Arabia, the anthropogenic fraction were relatively high (0.3 to 0.4) and regionally averaged anthropogenic fraction over India was 0.62±0.06 in 2004. This study indicates that multi-satellite observations can provide a powerful tool in monitoring air quality. We have noticed that anthropogenic fraction was 0.62 in 2004 and reduced to 0.43 in 2008. Major anthropogenic aerosol over India is BC and decreasing trend in BC could be one of the reasons for the decrease in anthropogenic fraction from 2004 to 2008. The CHIMERE chemistry-transport model was used to simulate PM, BC and AOD over India and are compared with measurements. Evaluation of CHIMERE output shows that diurnal and seasonal trends are captured reasonably well by the model. It was found that absolute magnitudes differ substantially during pre-monsoon and monsoon months. Presence of elevated aerosol layers during these seasons could be one of the sources for such discrepancy. Model simulations of anthropogenic fraction over Indian region are compared with observations and found good agreement. Results from this thesis moves us one step forward to reduce the uncertainties involved in anthropogenic aerosol fraction, its spatial and temporal distributions and regional distribution of OC/BC ratio, which are most important parameters in order to assess the climate forcing by anthropogenic aerosols.2014-12-10T18:30:00ZObserved Subseasonal Variability Of Temperarture And Salinity In The Tropical Indian Oceanhttp://hdl.handle.net/2005/2040
Title: Observed Subseasonal Variability Of Temperarture And Salinity In The Tropical Indian Ocean
Authors: Parampil, Sindu Raj
Abstract: Subseasonal variability of tropical Indian Ocean sea surface temperature is thought to influence the active-break cycle of the Asian monsoon. There are several open questions related to the role of surface fluxes, large-scale ocean circulation and subsurface ocean processes in the subseasonal variability of upper ocean temperature. We present a unified study of the subseasonal (2-90 day) variability of surface heat flux and upper ocean temperature and salinity throughout the tropical Indian Ocean in all seasons. We focus on the relation between surface fluxes and ocean response using a new satellitebased
daily heat flux. The role of ocean processes (advection, entrainment and mixing)
in determining SST variability is diagnosed from the daily satellite SST.
Before the onset of the summer monsoon, sea surface temperature (SST) of the north Indian Ocean warms to 30-32oC. Climatological mean mixed layer depth in spring (March-May) is 10-20 m, and net surface heat flux (Qnet) is 80-100 Wm􀀀2 into the ocean. It has been suggested that observed spring SST warming is small mainly due to (a) penetrative flux of solar radiation through the base of the mixed layer (Qpen), (b) advective cooling by upper ocean currents and (c) entrainment of sub-mixed layer cool water. We estimate the role of the first two processes in SST evolution from a two-week ARMEX experiment in April-May 2005 in the the southeastern Arabian Sea. The upper ocean is stratified by salinity and temperature, and mixed layer depth is shallow (6 to 12 m). Current speed at 2 m depth is high even under light winds. Currents within the mixed layer are quite distinct from those at 25 m. On subseasonal scales, SST warming is followed by rapid cooling. The cooling occurs although the ocean gains heat at the surface - Qnet is about 105 Wm􀀀2 in the warming phase, and 25 Wm􀀀2 in the cooling phase; penetrative loss Qpen, is 80 Wm􀀀2 and 70 Wm􀀀2. In the warming phase, SST rises mainly due to heat absorbed within the mixed layer, i.e. Qnet minus Qpen; Qpen, reduces the rate of SST warming by a factor of three. In the
second phase, SST cools rapidly because (a) Qpen, is larger than Qnet, and (b) advective cooling is _85 Wm􀀀2. A calculation using time-averaged heat fluxes and mixed layer depth suggests that diurnal variability of fluxes and upper ocean stratification tends to warm SST on subseasonal time scale. Buoy and satellite data suggest that a typical premonsoon intraseasonal SST cooling event occurs under clear skies and weak winds, when the ocean is gaining heat. In this respect, premonsoon SST cooling in the north Indian ocean is different from that due to MJO or monsoon ISO.
As a follow-up to ARMEX, we use a short dataset from a field campaign in the
premonsoon north Bay of Bengal to study diurnal variability of SST. In addition to the standard meteorological and hydrographic parameters measured from shipborne instruments and buoy sensors, we obtained a two-hourly record of subsurface sunlight profiles. Heat fluxes are seen to drive the SST warming during the day while both advection and entrainment/mixing are important during the night. The simple heat balance based on heat flux shows that it drives the diurnal cycle of SST, though ocean processes contribute towards night time cooling; this has been confirmed using the Price-Weller-Pinkel mixing model forced by heat flux and wind stress. A similar analysis for mixed layer salinity revealed that the salt balance in the region is dominated by advection rather than freshwater flux or entrainment/mixing.
Buoy and satellite data show pronounced subseasonal oscillations of sea surface
temperature (SST) in the summertime north Indian Ocean. The SST oscillations are forced mainly by surface heat flux associated with the active-break cycle of the south Asian summer monsoon. The input of freshwater (FW) from summer rain and rivers to the Bay is large, but not much is known about subseasonal salinity variability. We use 2002-2007 observations from Argo floats with 5-day repeat cycle to study the subseasonal response of temperature and salinity to surface heat and freshwater flux in the central Bay of Bengal and central Arabian Sea. Estimates of surface heat and freshwater flux are based on daily satellite data sampled along the float trajectory. We find that intraseasonal variability (ISV) of mixed layer temperature is mainly a response to net surface heat flux minus penetrative radiation during the summer monsoon season. In winter and spring, however, temperature variability appears to be mainly due to
ocean processes rather than local heat flux. Variability of mixed layer freshwater content is generally independent of local surface flux (precipitation minus evaporation) in all seasons. There are occasions when intense monsoon rainfall leads to local freshening, but these are rare. The large subseasonal fluctuations observed in FW appear to be due to advection, suggesting that freshwater from rivers and rain moves in eddies or filaments.
We have developed a new daily satellite-based heat flux dataset for the tropical Indian Ocean (30oE 􀀀 120oE; 30oS 􀀀 30oN); satellite data include surface air temperature and relative humidity from the Atmospheric Infrared Sounder (AIRS). On the seasonal scale (> 90 days) the flux compares reasonably well with climatologies and other daily data. On the subseasonal scale, our flux product has realistic behaviour relative to buoy data at validation sites. An important result is that ocean processes (advection, entrainment/detrainment, mixing at the base of the mixed layer) cool the tropical Indian Ocean SST by 8oC over the year. The largest contribution of ocean processes (_20oC SST cooling over the year) is in the western equatorial Indian Ocean. Ocean processes generally cool the upper ocean in all seasons and all regions, except in boreal winter, when they warm the north Indian Ocean. This is likely due to entrainment of
warm sub-mixed layer water in regions of inversions.
On subseasonal (2-90 days) scales, the contribution of air temperature and humidity to latent heat flux is roughly equal to the contribution from wind speed variability: Another interesting finding is that the contribution of air temperature and humidity increases away from the equator. One of the most important contributions of this thesis is the demonstration that tropical Indian Ocean SST has a coherent response to intraseasonal changes in heat flux associated with organised convection in the summer hemisphere. SST responds to flux in (i) the northeast Indian Ocean during May-October and (ii) the 15oS-5oN region during November-April. In the winter hemisphere and in regions with no organised convection, it is ocean processes and not fluxes which drive the subseasonal changes in SST. This result suggests that SST ISV feeds back to organise and sustain organised convection in the tropical atmosphere.2013-06-09T18:30:00ZDifference In Land-Ocean Response And The Regional Impact Of Geo-Engineeringhttp://hdl.handle.net/2005/1658
Title: Difference In Land-Ocean Response And The Regional Impact Of Geo-Engineering
Authors: Nag, Bappaditya2012-04-22T18:30:00ZFine-Scale Structure Of Diurnal Variations Of Indian Monsoon Rainfall : Observational Analysis And Numerical Modelinghttp://hdl.handle.net/2005/980
Title: Fine-Scale Structure Of Diurnal Variations Of Indian Monsoon Rainfall : Observational Analysis And Numerical Modeling
Authors: Sahany, Sandeep
Abstract: In the current study, we have presented a systematic analysis of the diurnal cycle of rainfall over the Indian region using satellite observations, and evaluated the ability of the Weather Research and Forecasting Model (WRF) to simulate some of the salient features of the observed diurnal characteristics of rainfall. Using high resolution simulations, we also investigate the underlying mechanisms of some of the observed diurnal signatures of rainfall. Using the Tropical Rain-fall Measuring Mission (TRMM) 3-hourly, 0.25 ×0.25 degree 3B42 rainfall product for nine years (1999-2007), we extract the finer spatial structure of the diurnal scale signature of Indian summer monsoon rainfall. Using harmonic analysis, we construct a signal corresponding to diurnal and sub-diurnal variability. Subsequently, the 3-hourly time-period or the octet of rain-fall peak for this filtered signal, referred to as the “peak octet,” is estimated with care taken to eliminate spurious peaks arising out of Gibbs oscillations. Our analysis suggests that over the Bay of Bengal, there are three distinct modes of the peak octet of diurnal rainfall corresponding to 1130, 1430 and 1730 IST, from north central to south Bay. This finding could be seen to be consistent with southward propagation of the diurnal rainfall pattern reported by earlier studies. Over the Arabian sea, there is a spatially coherent pattern in the mode of the peak octet (1430 IST), in a region where it rains for more than 30% of the time. In the equatorial Indian Ocean, while most of the western part shows a late night/early morning peak, the eastern part does not show a spatially coherent pattern in the mode of the peak octet, owing to the occurrence of a dual maxima (early morning and early/late afternoon). The Himalayan foothills were found to have a mode of peak octet corresponding to 0230 IST, whereas over the Burmese mountains and the Western Ghats (west coast of India) the rainfall peaks during late afternoon/early evening (1430-1730 IST). This implies that the phase of the diurnal cycle over inland orography (e.g., Himalayas) is significantly different from coastal orography (e.g., Western Ghats). We also find that over the Gangetic plains, the peak octet is around 1430 IST, a few hours earlier compared to the typical early evening maxima over land.
The second part of our study involves evaluating the ability of the Weather Research and Fore-casting Model (WRF) to simulate the observed diurnal rainfall characteristics. It also includes conducting high resolution simulations to explore the underlying physical mechanisms of the observed diurnal signatures of rainfall. The model (at 54km resolution) is integrated for the month of July 2006 since this period was particularly favourable for the study of diurnal cycle. We first evaluate the sensitivity of the model to the prescribed sea surface temperature (SST) by using two different SST datasets, namely Final Analyses (FNL) and Real-time Global (RTG). The overall performance of RTG SST was found to be better than FNL, and hence it was used for further model simulations. Next, we investigated the impact of different parameterisations (convective, microphysical, boundary layer, radiation and land surface) on the simulation of diurnal cycle of rainfall. Following this sensitivity study, we identified the suite of physical parameterisations in the model that “best” reproduces the observed diurnal characteristics of Indian monsoon rainfall.
The “best” model configuration was used to conduct two nested simulations with one-way, three-level nesting (54-18-6km) over central India and Bay of Bengal. While the 54km and 18km simulations were conducted for July 2006, the 6km simulation was carried out for the period 18-24 July 2006. This period was chosen for our study since it is composed of an active period (19-21 July 2006), followed by a break period (22-24 July 2006). At 6km grid-spacing the model is able to realistically simulate the active and break phases in rainfall. During the chosen active phase, we find that the observed rainfall over central India tends to reach a maximum in the late night/early morning hours. This is in contrast to the observed climatological diurnal maxima of late evening hours. Interestingly, the 6km simulation for the active phase is able to reproduce this late night/early morning maxima. Upon further analysis, we find that this is because of the strong moisture convergence at the mid-troposphere during 2030-2330 IST, leading to the rainfall peak seen during 2330-0230 IST. Based on our analysis, we conclude that during both active and break phases of summer monsoon, mid-level moisture convergence seems to be one of the primary factors governing the phase of the diurnal cycle of rainfall. Over the Bay of Bengal, the 6km model simulation is in very good agreement with observations, particularly during the active phase. The southward propagation observed during 19-20 July 2006, which was not captured by the coarse resolution simulation (54km), is exceedingly well captured by the 6km simulation. The positive anomalies in specific humidity attain a maxima during 2030-0230 IST in the north and during 0830-1430 IST in the south. This confirms the role of moisture convergence in the southward propagation of rainfall. Equally importantly we find that while low level moisture convergence is dominant in the north Bay, it is the mid-level moisture convergence that is predominant in the south Bay.2010-12-30T18:30:00Z